• Journal of Information Processing Systems
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• v.4 no.4
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• pp.159-168
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• 2008

Human-Robot Interaction (HRI), based on already well-researched Human-Computer Interaction (HCI), has been under vigorous scrutiny since recent developments in robot technology. Robots may be more successful in establishing common ground in project-based education or foreign language learning for children than in traditional media. Backed by its strong IT environment and advances in robot technology, Korea has developed the world's first available e-Learning home robot. This has demonstrated the potential for robots to be used as a new educational media - robot-learning, referred to as 'r-Learning'. Robot technology is expected to become more interactive and user-friendly than computers. Also, robots can exhibit various forms of communication such as gestures, motions and facial expressions. This study compared the effects of non-computer based (NCB) media (using a book with audiotape) and Web-Based Instruction (WBI), with the effects of Home Robot-Assisted Learning (HRL) for children. The robot gestured and spoke in English, and children could touch its monitor if it did not recognize their voice command. Compared to other learning programs, the HRL was superior in promoting and improving children's concentration, interest, and academic achievement. In addition, the children felt that a home robot was friendlier than other types of instructional media. The HRL group had longer concentration spans than the other groups, and the p-value demonstrated a significant difference in concentration among the groups. In regard to the children's interest in learning, the HRL group showed the highest level of interest, the NCB group and the WBI group came next in order. Also, academic achievement was the highest in the HRL group, followed by the WBI group and the NCB group respectively. However, a significant difference was also found in the children's academic achievement among the groups. These results suggest that home robots are more effective as regards children's learning concentration, learning interest and academic achievement than other types of instructional media (such as: books with audiotape and WBI) for English as a foreign language.

• The Journal of the Convergence on Culture Technology
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• v.6 no.1
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• pp.489-494
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• 2020

We propose to designs and to implements a robot analyzing the risk of occurrence of mental disorder of single-person households' workers through the facial expression-detecting system. Due to complex social factors, the number and proportion of single-person households continues to increase. In addition, contrast to the household of many family members, the prevalence of mental disorder among single-person household varies greatly. Since most patients with mental can not detect the disease on their own, counseling and treatment with doctors are often ignored. In this study, we design and implement a robot analyzing the risk of mental disorder of single-person households workers by constructing a system with Q.bo One, a social robot created by Thecorpora. Q.bo One is consisted of Arduino, ar raspberry pie, and other sensors designed to detect and respond to sensors in the direction users want to implement. Based on the DSM-5 provided by the American Psychiatric Association, the risk of mental disorder occurrence was specified based on mental disorder. Q.bo One analyzed the facial expressions of the subjects for a week or two to evaluate depressive disorder, anxiety disorder. If the mental disorder occurrence risk is high, Q.bo One is designd to inform the subject to counsel and have medical treatment with a specialist.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.1
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• pp.20-26
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• 2008

As they have more and more intelligence robots or computers these days, so the interaction between intelligence robot(computer) - human is getting more and more important also the emotion recognition and expression are indispensable for interaction between intelligence robot(computer) - human. In this paper, firstly we extract emotional features at speech signal and facial image. Secondly we apply both BL(Bayesian Learning) and PCA(Principal Component Analysis), lastly we classify five emotions patterns(normal, happy, anger, surprise and sad) also, we experiment with decision fusion and feature fusion to enhance emotion recognition rate. The decision fusion method experiment on emotion recognition that result values of each recognition system apply Fuzzy membership function and the feature fusion method selects superior features through SFS(Sequential Forward Selection) method and superior features are applied to Neural Networks based on MLP(Multi Layer Perceptron) for classifying five emotions patterns. and recognized result apply to 2D facial shape for express emotion.

• Fashion & Textile Research Journal
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• v.25 no.2
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• pp.248-254
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• 2023

This study aims to measure the skin rigidity of different facial areas among Koreans and propose guidelines for each area's skin rigidity that can be applied with a facial robot for testing respiratory protective devices. The facial skin rigidity of 40 participants, which included 20 men and 20 women, aged 20 to 50, was analyzed. The rigidity measurement was conducted in 13 facial areas, including six areas in contact with the mask and seven non-contact areas, by referring to the facial measurement guidelines of Size Korea. The facial rigidity was measured using the Durometer RX-1600-OO while in a supine position. The measurement procedure involved contacting the durometer vertically with the reference point, repeating the measurement of the same area five times, and using the average of three values whose variability was between 0.4 and 4.2 Shore OO. The rigidity data analysis used precision analysis, descriptive statistics analysis, and mixed-effect ANOVA. The analysis confirmed the rigidity of the 13 measurement areas, with the highest rigidity of the face being at the nose and forehead points, with values of 51.2 and 50.8, respectively, and the lowest rigidity being at the chin and center of the cheek points, with values of 19.2 and 20.7, respectively. Significant differences between gender groups were observed in four areas: the tip of the nose, the point below the chin, the area below the lower jaw, and the inner concha.

• The Journal of the Korea Contents Association
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• v.13 no.8
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• pp.109-117
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• 2013

This research is for selection of animal and establishment of guideline which for animal robot design for the purpose of emotionally disturbed children's psychotherapy. In the case of emotionally disturbed children because of poor expression about themselves's emotional condition, there are many restriction in the existing cure and educational method. Using research method of animal shape robot which is starting to make attempt since the late 1990s is effective to learning disturbed children. For the development of animal robot for psychotherapy of emotionally disturbed children first of all which animal is selected is very important. Therefore at the early stage of research preference surveyed to children including emotionally disturbed children and decide an object of animal robot. And what kind of shape is very preferred is also preference surveyed. Through focusing group interview about shape, color, facial expression, sound, and move which have an influence on outward shape design of robot, present the guideline which is needed to animal robot design for emotionally disturbed children.

• The Journal of Korea Robotics Society
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• v.10 no.2
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• pp.61-69
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• 2015

In this paper, we propose and examine the feasibility of the robot-assisted behavioral intervention system so as to strengthen positive response of the children with autism spectrum disorder (ASD) for learning social skills. Based on well-known behavioral treatment protocols, the robot offers therapeutic training elements of eye contact and emotion reading respectively in child-robot interaction, and it subsequently accomplishes pre-allocated meaningful acts by estimating the level of children's reactivity from reliable recognition modules, as a coping strategy. Furthermore, for the purpose of labor saving and attracting children's interest, we implemented the robotic stimulation configuration with semi-autonomous actions capable of inducing intimacy and tension to children in instructional trials. From these configurations, by evaluating the ability of recognizing human activity as well as by showing improved reactivity for social training, we verified that the proposed system has some positive effects on social development, targeted for preschoolers who have a high functioning level.

• Proceedings of the Korean Society of Computer Information Conference
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• 2013.01a
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• pp.201-204
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• 2013

디지털 컨텐츠의 종류와 양이 폭발적으로 증가하면서 컨텐츠 선호도 투표는 강한 파급력을 지니게 되었다. 하지만 컨텐츠 소비자가 직접 투표를 해야 하는 현재의 방법은 사람들의 투표 참여율이 저조하며, 조작 위험성이 높다는 문제점이 있다. 이에 본 논문에서는 컨텐츠 소비자의 얼굴 표정에 드러나는 감정을 인식함으로써 자동으로 컨텐츠 선호도를 추론하는 시스템을 제안한다. 본 논문에서 제안하는 시스템은 기존의 수동 컨텐츠 선호도 투표 시스템의 문제점인 컨텐츠 소비자의 부담감과 번거로움, 조작 위험성 등을 해소함으로써 보다 편리하고 효율적이며 신뢰도 높은 서비스를 제공하는 것을 목표로 한다. 따라서 본 논문에서는 컨텐츠 선호도 추론 시스템을 구축하기 위한 방법을 구체적으로 제안하고, 실험을 통하여 제안하는 시스템의 실용성과 효율성을 보인다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2019.11a
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• pp.128-130
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• 2019

최근 딥러닝의 급격한 발전과 함께 얼굴표정 인식(facial expression recognition) 기술이 상당한 진보를 이루었다. 얼굴표정 인식은 컴퓨터 비전 분야에서 지속적으로 관심을 받고 있으며, 인포테인먼트 시스템(Infotainment system), 인간-로봇 상호작용(human-robot interaction) 등 다양한 분야에서 활용되고 있다. 그럼에도 불구하고 얼굴표정 인식 분야는 학습 데이터의 부족, 얼굴 각도의 변화 또는 occlusion 등과 같은 많은 문제들이 존재한다. 본 논문은 얼굴표정 인식 분야에서의 위와 같은 고유한 문제들을 다룬 기술들을 포함하여 고전적인 기법부터 최신 기법에 대한 연구 동향을 제시한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.3
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• pp.754-774
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• 2023

Wrestling is one of the popular events for modern sports. It is difficult to quantitatively describe a wrestling game between athletes. And deep learning can help wrestling training by human recognition techniques. Based on the characteristics of latest wrestling competition rules and human recognition technologies, a set of wrestling competition video analysis and retrieval system is proposed. This system uses a combination of literature method, observation method, interview method and mathematical statistics to conduct statistics, analysis, research and discussion on the application of technology. Combined the system application in targeted movement technology. A deep learning-based facial recognition psychological feature analysis method for the training and competition of classical wrestling after the implementation of the new rules is proposed. The experimental results of this paper showed that the proportion of natural emotions of male and female wrestlers was about 50%, indicating that the wrestler's mentality was relatively stable before the intense physical confrontation, and the test of the system also proved the stability of the system.

• Proceedings of the Korea Contents Association Conference
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• 2019.05a
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• pp.183-184
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• 2019

본 논문에서는 로봇과 사람의 자연스러운 감정 소통을 위한 비디오 시퀀스 표정생성 대화 시스템을 제안한다. 제안된 시스템에서는 실시간 비디오 데이터로 판단된 관객의 감정 상태를 반영한 대답을 하며, 딥러닝(Deep Learning)을 활용하여 대화의 맥락에 맞는 로봇의 표정을 실시간 생성한다. 본 논문에서 관객의 표정을 위해 3만여개의 비디오 데이터로 학습한 결과 88%의 학습 정확도로 표정 생성이 가능한 것으로 확인되었다. 본 연구는 로봇 표정 생성에 딥러닝 방식을 적용한 것에 그 의의가 있으며 향후 대화 시스템 자체에도 딥러닝 방식을 확대 적용하기 위한 초석이 될 수 있다는 점에 의의가 있다.